A data warehouse can be used to store vast amounts of information or data including transactional/operational data. Data warehouse professionals including implementers and developers implement and maintain the data warehouse.
Data warehouse professionals also perform processes, referred to as a business data discovery process and a data discovery process, throughout the life of the data warehouse to ascertain the customer specific information/data required to build, run and maintain the data warehouse. The business discovery process is used to identify and record a set of specific customer related business problems. The data discovery process is used to establish customer related data available to solve such problems. The results from the business discovery process and the data discovery process each form an essential foundation of information upon which the data warehouse is built and operated.
During the business discovery process, the data warehouse professional identifies the customer's business goals, objectives, and problems to determine the types of problems that should or can be solved using the data warehouse. The data warehouse professional identifies the nature and availability of all data/information relating to the customer that can potentially serve as a basis for business analysis after being warehoused. The data discovery process is used to identify quantitatively and qualitatively the data sources of the customer's transactional/operational business related data. Data for the data warehouse is typically copied or derived from these data sources.
Exemplary data discovery information includes the types of devices serving as data warehouse data sources and the geographical locations of such devices, who administers the data source devices, the frequency with which the data source devices are updated or backed-up, the logical description of data stored by the data source devices and the access techniques or data transfer methods used to communicate data to and from the data source devices, and the business rationale for using such data (determined from the business discovery process). Data discovery information also includes defining the data or what the data means to the customer. For example, an end date in a billing table could mean the last date of service of the last date the customer was billed or both.
Data warehouse professionals typically perform the business discovery process and the data discovery process through a series of engagements with the customer. An engagement is a personal interaction between the data warehouse professionals and the customer, wherein the data warehouse professional solicits the business discovery information and the data discovery information from the customer and seeks to document relevant, discovered information. An engagement can last up to several months enabling the data warehouse professionals to gather the large amount of discovery data required to build and run a large data warehouse.
During a data warehouse engagement, many interactions occur between the customer and the data warehouse professionals. The information flow between the customer and the data warehouse professionals are intensive and spontaneous. Critical information and learned knowledge which are a result of these engagements may be lost if an automated process is not used to capture the transactions. To the inventors' knowledge, no such tool exists for documenting the engagement process used in creating and maintaining the data warehouse.